Investigation of the effect of a coupled land-atmosphere satellite data assimilation system on land-atmosphere processes

The objective of this study is to develop a new downscaling approach, which can take into account atmospheric and land surface heterogeneities for a better precipitation prediction. We address the effect of land surface heterogeneity on the land-atmosphere interactions through coupling a land data assimilation system with a land-atmosphere coupled model. This system relies on a mesoscale model as the atmospheric part, a Land Surface Scheme as a model operator, a Radiative Transfer Model as an observation operator, satellite data and the Simulated Annealing method for minimization. To assess the effectiveness of the new system, two-dimensional numerical experiments were carried out in a mesoscale area of the Tibetan Plateau for dry and wet seasons. The results showed significant differences compared with standard regional atmospheric model outputs and were more consistent with satellite microwave brightness temperature observations. The latter induced an improvement of the spatial distribution of soil moisture, which strongly affected the convection systems.